Off-the-shelf software component reuse in a cloud computing environment

ABSTRACT

A computer-implemented distributed data processing method for a software application that includes no code that targets a distributed data processing system, the method including in a first process executing a first software component on a first computer, establishing a reference to at least a second software component resident on a second computer, establishing a handler in a second process executing on the second computer, determining that the first process is attempting to invoke a routine of the second software component based on the handler, and transferring data from the first process to the second process.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a Continuation Application of U.S. patentapplication Ser. No. 16/287,174, filed on Feb. 27, 2019, which is aContinuation Application of U.S. patent application Ser. No. 15/469,748,filed on Mar. 27, 2017, now U.S. Pat. No. 10,303,507, issued on May 28,2019, the entire contents of which are hereby incorporated by reference.

BACKGROUND

The present invention relates generally to a distributed data processingmethod for application software, and more particularly, but not by wayof limitation, to a system, method, and computer program product fordistributing processes for computation beyond the limits of theirvirtual address spaces by offloading their in-memory components acrossnodes.

Most cloud computing systems rely on hardware virtualization to emulatethe behavior of one or another off-the-shelf platform, often onheterogeneous real hardware. A drawback of this virtual machine (“VM”)based approach is the waste of resources entailed by replication ofsoftware components from VM to VM. When different applications runningon different VMs share the resources of a cloud or other distributedcomputing environment, each of them requires its own services, devicedrivers, shared libraries, etc. It would be advantageous for all suchcomponents to be reusable and shared by all the applications that run ina cloud system.

Typically, the various components accessible by a distributed operatingsystem reside within a cluster of nodes. However, the conventionaltechniques for distributed operating systems do not provide foroff-the-shelf software to be distributed onto such a system, but ratherlimit any software designed without distributed computing in mind toexecute only on a single computing node within the distributed computingenvironment. To date, distributed operating systems do not at all lendthemselves to running ordinary software in a distributed manner becauseof drawbacks in the various techniques.

There is a need in the art for a system that allows off-the-shelfsoftware, intended for execution on a conventional operating system, tobe distributed across nodes without requiring a special rebuild orversion. Further, there is a need for application software and/orservices to be able to invoke components that run on various nodes, inorder to achieve fairly balanced component deployment across nodes andto avoid duplicative component deployments from node to node, allwithout the application software or services necessarily being awarethat they are running on a distributed system. If such a system weremade available, software could then be tested bringing all the tools andtechniques usable on conventional operating systems to bear. Ordinarysoftware could then be distributed within a cloud computing environmentin a more highly scalable manner than can be achieved via conventionalhardware virtualization alone.

SUMMARY

In an exemplary embodiment, the present invention can provide acomputer-implemented distributed data processing method for a softwareapplication that includes no code that targets a distributed dataprocessing system, the method including in a first process executing afirst software component on a first computer, establishing a referenceto at least a second software component resident on a second computer,establishing a handler in a second process executing on the secondcomputer, determining that the first process is attempting to invoke aroutine of the second software component, transferring data from thefirst process to the second process, arranging for the first process toawait a response from the second process, and invoking, by the secondprocess, the routine of the second software component; and providing, bythe second process, the response to the first process. One or more otherexemplary embodiments include a computer program product and a system,based on the method described above.

Other details and embodiments of the invention will be described below,so that the present contribution to the art can be better appreciated.Nonetheless, the invention is not limited in its application to suchdetails, phraseology, terminology, illustrations and/or arrangements setforth in the description or shown in the drawings. Rather, the inventionis capable of embodiments in addition to those described and of beingpracticed and carried out in various ways that should not be regarded aslimiting.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may readily be utilized as a basisfor the desiring of other structures, methods and systems for carryingout the several purposes of the present invention. It is important,therefore, that the claims be regarded as including such equivalentconstructions insofar as they do not depart from the spirit and scope ofthe present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the invention will be better understood from the followingdetailed description of the exemplary embodiments of the invention withreference to the drawings, in which:

FIG. 1 exemplarily shows a high-level flow chart for a distributed dataprocessing method 100 according to an embodiment of the presentinvention;

FIG. 2 exemplarily depicts how off-the-shelf components designed to loadinto a single process are distributed across nodes without necessarilyrequiring the overhead created by hardware virtualization;

FIG. 3 exemplarily depicts a process overview for a first node;

FIG. 4 depicts a cloud-computing node 10 according to an embodiment ofthe present invention;

FIG. 5 depicts a cloud-computing environment 50 according to anembodiment of the present invention; and

FIG. 6 depicts abstraction model layers according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The invention will now be described with reference to FIGS. 1-6, inwhich like reference numerals refer to like parts throughout. It isemphasized that, according to common practice, the various features ofthe drawings are not necessarily to scale. On the contrary, thedimensions of the various features can be arbitrarily expanded orreduced for clarity.

By way of introduction of the example depicted in FIG. 1, an embodimentof a distributed data processing method 100 according to the presentinvention can include various steps for allowing for a softwareapplication that has been designed with single-node operation in mind tooperate in a distributed fashion by automatically arranging forcomponents of the application to execute across multiple nodes.

By way of introduction of the example depicted in FIG. 4, one or morecomputers of a computer system 12 according to an embodiment of thepresent invention can include a memory 28 having instructions stored ina storage system to perform the steps of FIG. 1.

With reference generally to the embodiments of the invention, when auser or service is authenticated to the system, one of the nodesresponds by providing a user interface or a service managementinterface. The user or service can launch a process. The process maylaunch on any node. The process may attempt to load software components,which may (unbeknownst to it) load on any other node. Calls to thosecomponents can be directed to the appropriate node via one or morethunks that reference a directory of components installed on a remotecomputer and/or one or more components resident or loaded on a remotecomputer.

A thunk comprises one or more routines, data structures, or objects usedto provide an interface outside of the system's ordinary callingmechanism. An embodiment can use a thunk, either individually or in acollective known as a thunk layer, to redirect calls between components,such that a call intended for a component that might have been loadedinto the address space of a process is redirected to a component runningin a separate address space of a separate process running on a separateprocessor. In various embodiments, the thunk or thunk layer can beestablished via system call interception, hooks, or operating systemintervention. System call interception can be arranged via codeinstrumentation, such as by instructions inserted into object code orbyte code. Hooks can be arranged via platform-dependent code such as theSetWindowsHookEx( ) API function provided on the Microsoft Windows®platform. Operating system intervention can be arranged via variousmeans that will be apparent to those who possess ordinary skill in theart, such as a loader modification that can identify a component thatmay reside on a separate node. The thunk or thunk layer can beestablished by one of these or other means in accordance with theinventive arrangements disclosed herein. Thus the invention can beembodied via application software, a service, a device driver, anoperating system loader, or another operating system component orcomponents suitable for carrying out the several purposes of theinvention.

Virtual memory from the original process may be referenced by the nodesvia a page fault that triggers the copying of pages from the process ondemand. A page fault is an exception or interrupt that occurs when aprocess attempts to access virtual memory that is not mapped to physicalmemory. Conventional operating systems typically handle a page fault byloading a page from disk into memory. In embodiments, updates to thepages can be transferred back to the originating process, either in realtime or at the time when control is returned to the calling routine inthe originating process. The invention's only performance cost will bethat of arranging the needed transparent inter-process communication andpage-fault handling between nodes.

Software components, such as dynamically loadable modules, are set up toreside on suitable nodes, for example, nodes that handle other similarcomponents or components related to a given software package or bundle,whenever software is installed. Some administrator insight may be neededto select a node on which a particular component, or set of components,will reside. Otherwise, once software is installed, further special userintervention is not required (e.g., to run and load applications andcomponents). A directory of installed components and their correspondingnodes can be maintained automatically. Software runs, from a user oradministrator perspective, in just the manner it normally would run.Other than software installer aspects that may prompt a user oradministrator to choose nodes on which to install or load componentsthat will be available to processes running on the distributed system,the inventive arrangements disclosed herein, including those of thefollowing paragraphs, take place “beneath the covers”.

It is noted that a “component” as referred to herein is a softwarecomponent discretely operable on a distributed system and can include avirtual machine, a set of virtual machines, a hypervisor, an operatingsystem, an operating system service or device driver, an executableprogram, a module or library loadable by or linked with an executableprogram, an object, a set of objects, a code sequence, a function, amethod, a procedure, a thread, a fiber, a dynamic-link library (“DLL”),a shared object (“SO”), or any information, having an executable aspect,that may be discretely instantiated in a distributed context. In theexamples provided herein, unless otherwise indicated, a component may beconsidered to be a module that may be dynamically loaded by anexecutable program operable on a distributed system. The examplesprovided herein are not intended to limit the scope of the invention.

A thunk or thunk layer is incorporated into each process. The thunk orthunk layer can reference the component directory or information derivedfrom that directory. The thunk or thunk layer also can reference anyremote components, or routines made available by remote components,needed by the process. In lieu of loading executable component code intothe virtual memory for a process on a given node, a reference to thethunk is used to invoke a routine made available by that component via asynthesized remote procedure call (“sRPC”). Conventionally, a remoteprocedure call is arranged in a predetermined manner for participatingcomponents by a software developer, via compiler directives or via callsto API functions such as the RpcBindingCopy( ) function provided on theMicrosoft Windows® platform. In various embodiments, the sRPC can beautomatically arranged, as needed to intercept calls between componentsthat execute on disparate nodes, via calls to applicable API functionsfrom code invoked by or in tandem with the thunk or thunk layerdescribed hereinabove. As such, the sRPC can be arranged by applicationsoftware, a service, a device driver, an operating system loader, oranother operating system component or components suitable for carryingout the several purposes of the invention.

In some embodiments a service thread, created on the node where thecomponent resides, will handle the sRPC. In some embodiments, eachservice thread that handles sRPC processing can run in its own processwhose virtual address space is a virtual duplicate, in whole or in part,of the address space of the caller process. When sRPCs are generated bymultiple threads of a single caller process, then multiple servicethreads that handle the sRPCs can share the duplicate virtual addressspace corresponding to that caller process. In some embodiments, whenmultiple processes running on outboard nodes share a component, thenmultiple processes or service threads also can run on the node on whichthe component resides, each of which will handle the sRPC processing fora corresponding outboard process. In other embodiments, a single servicethread will determine which outboard process and thread is associatedwith each local process and thread, and will route calls from variousoutboard processes accordingly. In keeping with the various embodimentsdescribed hereinabove, a service thread can be created by applicationsoftware, a service, a device driver, an operating system loader, oranother operating system component suitable for carrying out the severalpurposes of the invention.

With reference to FIG. 2, if an sRPC specifies a component that has notyet been loaded, then the corresponding service thread can load thecomponent. In some embodiments, the component can be loaded into thevirtual address space of the process in which that service thread isrunning. To enable this functionality, the service thread will executecode that determines that the component is resident on the node butunloaded. If an error occurs in the loading of the component, then theservice thread can look to the directory of installed components to findany other nodes that may have backup copies of the component. If abackup copy is found, then another service thread, running on that nodewhere the backup component is resident, can be invoked to handle thesRPC. In the event that the component cannot load, or if its routinescannot be invoked by any service thread on the distributed system, thenthe system will arrange for the raising of an exception back in thecaller process on the originating node. That exception will be similarto any exception that would have been raised, had a component failed toload locally into the caller process, or to be invoked therefrom, on aconventional system. The thunk functionality described hereinabove caninclude the logic necessary for detecting failed sRPCs based on timeoutexpirations, error values returned from sRPC handlers, or other means,and raising the appropriate exceptions in the caller process.

When a service thread requires access to virtual memory belonging to thecaller process that is not present on the node where the componentresides, a page fault will result. Processing of the page fault willinvolve copying one or more pages from the caller process to the virtualaddress space available to the service thread on the node where thecomponent resides. A mechanism such as distributed shared virtual memorycan provide for copying those virtual memory pages.

When the service thread updates a virtual memory page that has beenshared with the first component, the system can arrange for thecorresponding page in the caller process on the originating node to be“dirty”. Any attempt by the caller process to access that page can thenresult in another page fault. A handler for the page fault will copy anyupdates made by the service thread back to caller process on theoriginating node. With reference to FIG. 3, once control returns from anoutboard component, accessing pages that have been allocated orcommitted on behalf of that component or updated by that component willtrigger further page faults; the system will then pull the allocated,committed, or updated pages into the address space of the callerprocess. In some embodiments, detection and handling of accesses todirty pages can be arranged by application software or a service ordriver that tracks inter-process interactions that happen via the thunkor thunk layer described hereinabove. Embodiments that rely onapplication software to intercept memory reads and writes and thusdiscover and track dirty pages can do so by various means known in theart. One means available to application software or other high-levelsoftware for this purpose includes object code insertion, byte codeinsertion, or other instrumentation designed to intercept all memoryaccesses. Another means comprises not committing, or storing and thendecommitting, memory pages. When a remote process attempts to access anydecommitted page, the high-level software can handle an exception raisedas a result of the attempt, by reloading the page either from the remoteprocess or from disk, depending on whether the page is dirty or not,respectively. Dirty pages can be stored to disk when control is returnedfrom a component to an outboard caller process, and the correspondingpages within the caller process can be decommitted by thunk code or by aroutine shared throughout the thunk layer. Shared disk storage may servefor storing decommitted pages and for reloading them into a process onany node that attempts to access them. In other embodiments, detectionand handling of accesses to dirty pages can be performed by one or moreoperating system components, such as versions of those operating systemcomponents that raise and handle conventional page faults onconventional systems, but extended to embody the page fault raising andhandling aspects of the invention.

In some embodiments, the set of service threads that handle sRPCprocessing can belong to one or more thread pools. A thread pool canprovide threads for sRPC processing on behalf of one or more componentsresiding on a node, or for all of the components residing on a node. Athread that has completed sRPC handling for a caller process can awaitfurther sRPC requests from that process or can be returned to the threadpool, to be redeployed as needed for the handling of sRPC invocationsfrom other callers. Threads that are no longer in use can be returned tothe pool based on a least-frequently-used model. Likewise, pages fromcaller processes that are no longer referenced can be evicted from anode based on a least-frequently-used model.

The shared memory ranges and page fault handlers can be set up based ona storage system that is shared by all of the participating nodes. Asystem that is set up according to the invention can run multipleprocesses concurrently on multiple nodes, sharing the same set ofcomponents among all of the processes. For any given number of realcomputers, such a system will be scalable to run more processes, and canprovide each process with more resources, than systems that relyentirely on conventional hardware virtualization arrangements to meetcloud computing needs.

With reference to FIG. 1, a computer-implemented distributed dataprocessing method 100 for a software application that includes no codethat targets a distributed data processing system is depicted.

In step 101, in a first process executing a first software component ona first computer, a reference is established to at least a secondsoftware component resident on a second computer; in some embodimentsthe reference can be a reference to a thunk object, data structure, orroutine.

In step 102, a handler is established in a second process executing onthe second computer; in some embodiments the handler can be an sRPChandler.

In step 103, it is determined that the first process is attempting toinvoke a routine of the second software component.

In step 104, data is transferred from the first process to the secondprocess; in some embodiments a thunk is used for data transfer; in someembodiments shared memory is used; in some embodiments an inter-processcommunication mechanism is used.

In step 105, arrangement is made for the first process to await aresponse from the second process; in some embodiments a caller thread ofthe first process can enter a wait state; in other embodiments theentire first process can wait; in yet other embodiments the firstprocess can continue executing in expectation of an interrupt or othersignal from the second process.

In step 106, by the second process, the routine of the second softwarecomponent is invoked; in some embodiments invocation is arranged via athunk.

In step 107, the second process provides the response to the firstprocess.

The above embodiments of the invention can provide at least thatinstalled software components are not duplicated across nodes, otherthan as may be necessary for redundancy/failover purposes. Anotherbenefit of the invention is that in-memory components are notduplicated, either; the in-memory executable code for a componentremains local to the node on which that component resides. Because athunk or thunk layer serves in lieu of loading a component into thevirtual memory of a caller process, the invention can enable adistributed computing model with no hardware virtualization, allowingthat caller process to greatly conserve virtual memory and eliminatingthe overhead associated with hardware virtualization itself and anyhypervisor, instruction set emulation, etc. Embodiments that areoperable in non-virtualized cloud computing platforms can thus supportmore processes than equivalent hardware-virtualized platforms, byconserving hardware resources. Off-the-shelf software also can fit intothe virtual address space that it expects to be available, whileeffectively loading more components than would normally fit into thatvirtual address space, without the need for developers to concernthemselves with distributed computing concepts or with rewritestargeting specialized distributed computing or cloud computingplatforms.

In other words, processes get to expand beyond the limits of theirvirtual address spaces by offloading their in-memory components acrossnodes. Without requiring virtual machines, for any given number ofnodes, the overall system can run more and bigger processes, on a givenset of nodes, than would be possible with a state of the art cloudcomputing environment that is based on conventional hardwarevirtualization. The invention also can be embodied in an environmentinvolving virtual machines. Certain benefits of the invention, such asallowing for components to not be replicated among virtual machines, canbe realized in such an environment. Further, the invention can beembodied in yet other environments and provide similar benefits.

Exemplary Aspects, Using an Embedded Computing Environment

Embedded systems are increasingly common in the Internet of Things(“IoT”) landscape and increasingly communicate with one another.Although this detailed description includes an exemplary embodiment ofthe present invention in an embedded/IoT computing environment, it is tobe understood that implementation of the teachings recited herein arenot limited to such an embedded/IoT computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of distributed computing environment nowknown or later developed.

Computing devices embedded in other devices or objects are typicallyrelatively simple with respect to general purpose computers such as thecloud-computing node 10 depicted in FIG. 4. As such, embedded computingdevices may not have the facilities necessary to support multithreadedoperation as described in other exemplary embodiments of the inventionas disclosed herein. Nonetheless, the invention may be embodied in a setof embedded computing devices, notwithstanding the lack of multithreadedoperation, so long as a set of embedded computing devices can otherwiseact as a distributed computing environment as described herein, and solong as the off-the-shelf software to be distributed across the set ofembedded computing devices comprises a set of components that each canindependently reside on any of the embedded computing devices among theset of embedded computing devices.

Each embedded computing device, among a set of such devices that eachact as members of a distributed computing environment, can provide auser interface or a service management interface. The user or servicecan interact with a process. The process may execute on any of theembedded computing devices in the set. The process may attempt to invokeroutines provided by software components that may reside on any otherembedded computing device in the set. Each call to a non-local componentcan be directed to the appropriate embedded computing device via a thunkthat references a directory of installed components. A thunk also canreference any routines of the non-local component as needed by theprocess.

An embodiment of the invention that relies on virtual memory managementprovided by the embedded computing devices can arrange for virtualmemory from the original process to be referenced by the embeddedcomputing devices via a page fault that triggers the copying of pagesfrom the process. Updates to the pages can be transferred back to theoriginating process, either in real time or at the time when control isreturned to the calling routine in the originating process. The embeddedcomputing device on which each software component resides can beautomatically tracked via a directory of components. Software runs, froma user or administrator perspective, in just the manner it normallywould run.

In other embodiments in which the embedded computing devices do notsupport virtual memory or paging on their own, a shared memory mechanismmay serve to allow for components operable on the various embeddedcomputing devices to transfer both control and memory updates among oneanother. Control can be transferred from a calling routine on anoriginating embedded computing device to a subroutine made available bya component, operable on a different device, that can provide updates toshared memory accessible by the originating device. The directory ofcomponents can automatically track not only the device on which eachsoftware component resides, but also the portion of shared memory usableby any pair of components among which control is transferred acrossdevices. Software runs, from a user or administrator perspective, in themanner it normally would run, albeit with a portion of the address spaceof each process reserved for the shared memory purposes made necessarygiven the lack of virtual memory support for such an embodiment.

For either of the embedded computing embodiments described above, athunk referencing the component directory or information derived fromthat directory is available to each embedded computing device. Areference to the thunk is used to invoke a routine made available bythat component via a call, such as a remote procedure call, that cantarget an embedded computing device that is programmed to handle it. Insome embodiments, the call can be as simple as an interrupt or othersignal that is associated with a shared memory region recognizable bythe embedded computing devices. When multiple embedded computing devicesshare a component, then all of the devices also will share thearrangement for handling the signal and associating it with theappropriate shared memory region, possibly with the assistance ofinformation in the component directory.

Exemplary Aspects, Using a Cloud Computing Environment

Although this detailed description includes an exemplary embodiment ofthe present invention in a cloud computing environment, it is to beunderstood that implementation of the teachings recited herein are notlimited to such a cloud computing environment. Rather, embodiments ofthe present invention are capable of being implemented in conjunctionwith any other type of distributed computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client circuits through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablenode and is not intended to suggest any limitation as to the scope ofuse or functionality of embodiments of the invention described herein.Regardless, cloud computing node 10 is capable of being implementedand/or performing any of the functionality set forth herein.

Although cloud computing node 10 is depicted as a computer system/server12, it is understood to be operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well-known computing systems, environments,and/or configurations that may be suitable for use with computersystem/server 12 include, but are not limited to, personal computersystems, server computer systems, thin clients, thick clients, hand-heldor laptop circuits, multiprocessor systems, microprocessor-basedsystems, set top boxes, programmable consumer electronics, network PCs,minicomputer systems, mainframe computer systems, and distributed cloudcomputing environments that include any of the above systems orcircuits, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingcircuits that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage circuits.

Referring now to FIG. 4, a computer system/server 12 is shown in theform of a general-purpose computing circuit. The components of computersystem/server 12 may include, but are not limited to, one or moreprocessors or processing units 16, a system memory 28, and a bus 18 thatcouples various system components including system memory 28 toprocessor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable Media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further described below, memory 28 mayinclude a computer program product storing one or program modules 42comprising computer readable instructions configured to carry out one ormore features of the present invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may be adapted for implementation in anetworking environment. In some embodiments, program modules 42 areadapted to generally carry out one or more functions and/ormethodologies of the present invention.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing circuit, other peripherals,such as display 24, etc., and one or more components that facilitateinteraction with computer system/server 12. Such communication can occurvia Input/Output (I/O) interface 22, and/or any circuits (e.g., networkcard, modem, etc.) that enable computer system/server 12 to communicatewith one or more other computing circuits. For example, computersystem/server 12 can communicate with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 20. As depicted,network adapter 20 communicates with the other components of computersystem/server 12 via bus 18. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system/server 12. Examples, include, but arenot limited to: microcode, circuit drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems, etc.

Referring now to FIG. 5, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing circuits used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingcircuit. It is understood that the types of computing circuits 54A-Nshown in FIG. 5 are intended to be illustrative only and that computingnodes 10 and cloud computing environment 50 can communicate with anytype of computerized circuit over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 6, an exemplary set of functional abstractionlayers provided by cloud computing environment 50 (FIG. 5) is shown. Itshould be understood in advance that the components, layers, andfunctions shown in FIG. 6 are intended to be illustrative only andembodiments of the invention are not limited thereto. As depicted, thefollowing layers and corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage circuits 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and distributed data processing method 100 inaccordance with the present invention.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), a Storage Area Network (SAN), a Network AttachedStorage (NAS) device, a Redundant Array of Independent Discs (RAID), anerasable programmable read-only memory (EPROM or Flash memory), a staticrandom access memory (SRAM), a portable compact disc read-only memory(CD-ROM), a digital versatile disk (DVD), a memory stick, a USB “thumb”drive, a mechanically encoded device such as punch-cards or raisedstructures in a groove having instructions recorded thereon, and anysuitable combination of the foregoing. A computer readable storagemedium, as used herein, is not to be construed as being transitorysignals per se, such as radio waves or other freely propagatingelectromagnetic waves, electromagnetic waves propagating through awaveguide or other transmission media (e.g., light pulses passingthrough a fiber-optic cable), or electrical signals transmitted througha wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

Further, Applicant's intent is to encompass the equivalents of all claimelements, and no amendment to any claim of the present applicationshould be construed as a disclaimer of any interest in or right to anequivalent of any element or feature of the amended claim.

What is claimed is:
 1. A computer-implemented distributed dataprocessing method for a software application that includes no code thattargets a distributed data processing system, the method comprising: ina first process executing a first software component on a firstcomputer, establishing a reference to at least a second softwarecomponent resident on a second computer, wherein virtual memory from thefirst process is referenced via a page fault and updates to a page inthe first process are transferred back to the first process from asecond process executing on the second computer.
 2. A computer programproduct for distributed data processing for a software application thatincludes no code that targets a distributed data processing system, thecomputer program product comprising a computer-readable storage mediumhaving program instructions embodied therewith, the program instructionsexecutable by a computer to cause the computer to perform: in a firstprocess, establishing a reference to a second software componentresident on a second computer, wherein virtual memory from the firstprocess is referenced via a page fault and updates to a page in thefirst process are transferred back to the first process from a secondprocess executing on the second computer.
 3. A distributed dataprocessing system for a software application that includes no code thattargets a distributed data processing system, said system comprising: aprocessor; and a memory, the memory storing instructions to cause theprocessor to perform: in a first process, establishing a reference to asecond software component resident on a second computer; andtransferring data from the first process to a second process executingon the second computer.
 4. The computer-implemented method of claim 1,further comprising: establishing a handler in a second process executingon the second computer; determining that the first process is attemptingto invoke a routine of the second software component based on thehandler; transferring data from the first process to the second process;and arranging for the first process to await a response from the secondprocess.
 5. The computer-implemented method of claim 4, furthercomprising invoking, by the second process, the routine of the secondsoftware component.
 6. The computer-implemented method of claim 5,further comprising providing, by the second process, the response to thefirst process.
 7. The computer-implemented method of claim 6, whereinthe transferring data from the first process to the second processcomprises transferring parameters that are passed between the firstsoftware component and the second software component as part of a callto a routine.
 8. The computer-implemented method of claim 7, Thecomputer-implemented method of claim 2, wherein an attempt by the secondsoftware component to access certain data established by the firstsoftware component generates the page fault.
 9. The computer-implementedmethod of claim 8, wherein a handler for the page fault transfers datafrom the first computer to the second computer.
 10. Thecomputer-implemented method of claim 6, wherein an attempt by the firstsoftware component to access certain data updated by the second softwarecomponent generates a page fault.
 11. The computer-implemented method ofclaim 10, wherein the handler for the page fault transfers data from thesecond computer to the first computer.
 12. The computer-implementedmethod of claim 1, embodied in a cloud-computing environment.
 13. Thecomputer-implemented method of claim 1, wherein duplicative deploymentof the first software component deployed on the second computer isavoided from another node in the distributed data processing system. 14.The computer-implemented method of claim 1, wherein the updates aretransferred either in real time or at a time when control is returned toa calling routine in an originating process.
 15. The computer programproduct of claim 2, wherein duplicative deployment of the first softwarecomponent deployed on the second computer is avoided from another nodein the distributed data processing system.
 16. The computer programproduct of claim 2, wherein the updates are transferred either in realtime or at a time when control is returned to a calling routine in anoriginating process.
 17. The system of claim 3, wherein duplicativedeployment of the first software process deployed on the second computeris avoided when the routine is invoked.
 18. The system of claim 3,wherein the transferring occurs either in real time or at a time whencontrol is returned to a calling routine in an originating process. 19.The computer program product of claim 3, further comprising:establishing a handler in a second process executing on the secondcomputer; determining that the first process is attempting to invoke aroutine of the second software component based on the handler;transferring data from the first process to the second process; andarranging for the first process to await a response from the secondprocess.
 20. The computer program product of claim 3, further comprisinginvoking, by the second process, the routine of the second softwarecomponent.